Esophageal adenocarcinoma (EAC) has a dismal prognosis, and survival benefits of recent multimodality treatments remain small. Cancer-associated fibroblasts (CAFs) are known to contribute to poor outcome by conferring therapy resistance to various cancer types, but this has not been explored in EAC. Importantly, a targeted strategy to circumvent CAF-induced resistance has yet to be identified. By using EAC patient-derived CAFs, organoid cultures, and xenograft models we identified IL-6 as the stromal driver of therapy resistance in EAC. IL-6 activated epithelial-to-mesenchymal transition in cancer cells, which was accompanied by enhanced treatment resistance, migratory capacity, and clonogenicity. Inhibition of IL-6 restored drug sensitivity in patient-derived organoid cultures and cell lines. Analysis of patient gene expression profiles identified ADAM12 as a noninflammation-related serum-borne marker for IL-6–producing CAFs, and serum levels of this marker predicted unfavorable responses to neoadjuvant chemoradiation in EAC patients. These results demonstrate a stromal contribution to therapy resistance in EAC. This signaling can be targeted to resensitize EAC to therapy, and its activity can be measured using serum-borne markers.

BackgroundThe upper gastrointestinal tract is home to some of most notorious cancers like esophagogastric and pancreatic cancer. Several factors contribute to the lethality of these tumors, but one that stands out for both tumor types is the strong inter- as well as intratumor heterogeneity. Unfortunately, genetic tumor models do not match this heterogeneity, and for esophageal cancer no adequate genetic models exist. To allow for an improved understanding of these diseases, tissue banks with sufficient amount of samples to cover the extent of diversity of human cancers are required. Additionally, xenograft models that faithfully mimic and span the breadth of human disease are essential to perform meaningful functional experiments.MethodsWe describe here the establishment of a tissue biobank, patient derived xenografts (PDXs) and cell line models of esophagogastric and pancreatic cancer patients. Biopsy material was grafted into immunocompromised mice and PDXs were used to establish primary cell cultures to perform functional studies. Expression of Hedgehog ligands in patient tumor and matching PDX was assessed by immunohistochemical staining, and quantitative real-time PCR as well as flow cytometry was used for cultured cells. Cocultures with Hedgehog reporter cells were performed to study paracrine signaling potency. Furthermore, SHH expression was modulated in primary cultures using lentiviral mediated knockdown.ResultsWe have established a panel of 29 PDXs from esophagogastric and pancreatic cancers, and demonstrate that these PDXs mirror several of the (immuno)histological and biochemical characteristics of the original tumors. Derived cell lines can be genetically manipulated and used to further study tumor biology and signaling capacity. In addition, we demonstrate an active (paracrine) Hedgehog signaling mode by both tumor types, the magnitude of which has not been compared directly in previous studies.ConclusionsOur established PDXs and their matching primary cell lines retain important characteristics seen in the original tumors, and this should enable future studies to address the responses of these tumors to different treatment modalities, but also help in gaining mechanistic insight in how some tumors respond to certain regimens and others do not.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0469-1) contains supplementary material, which is available to authorized users.

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers. However, divergent outcomes exist between patients, suggesting distinct underlying tumor biology. Here, we delineated this heterogeneity, compared interconnectivity between classification systems, and experimentally addressed the tumor biology that drives poor outcome. RNA-sequencing of 90 resected specimens and unsupervised classification revealed four subgroups associated with distinct outcomes. The worst-prognosis subtype was characterized by mesenchymal gene signatures. Comparative (network) analysis showed high interconnectivity with previously identified classification schemes and high robustness of the mesenchymal subtype. From species-specific transcript analysis of matching patient-derived xenografts we constructed dedicated classifiers for experimental models. Detailed assessments of tumor growth in subtyped experimental models revealed that a highly invasive growth pattern of mesenchymal subtype tumor cells is responsible for its poor outcome. Concluding, by developing a classification system tailored to experimental models, we have uncovered subtypespecific biology that should be further explored to improve treatment of a group of PDAC patients that currently has little therapeutic benefit from surgical treatment.